Parallelization of a Six Degree of Freedom Entry Vehicle Trajectory Simulation Using OpenMP and OpenACC

The art and science of writing parallelized software, using methods such as Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC), is dominated by computer scientists. Engineers and non-computer scientists looking to apply these techniques to their project applications face a steep learning curve, especially when looking to adapt their original single threaded software to run multi-threaded on graphics processing units (GPUs). There are significant changes in mindset that must occur; such as how to manage memory, the organization of instructions, and the use of if statements (also known as branching). The purpose of this work is twofold: 1) to demonstrate the applicability of parallelized coding methodologies, OpenMP and OpenACC, to tasks outside of the typical large scale matrix mathematics; and 2) to discuss, from an engineers perspective, the lessons learned from parallelizing software using these computer science techniques. This work applies OpenMP, on both multi-core central processing units (CPUs) and Intel Xeon Phi 7210, and OpenACC on GPUs. These parallelization techniques are used to tackle the simulation of thousands of entry vehicle trajectories through the integration of six degree of freedom (DoF) equations of motion (EoM). The forces and moments acting on the entry vehicle, and used by the EoM, are estimated using multiple models of varying levels of complexity. Several benchmark comparisons are made on the execution of six DoF trajectory simulation: single thread Intel Xeon E5-2670 CPU, multi-thread CPU using OpenMP, multi-thread Xeon Phi 7210 using OpenMP, and multi-thread NVIDIA Tesla K40 GPU using OpenACC. These benchmarks are run on the Pleiades Supercomputer Cluster at the National Aeronautics and Space Administration (NASA) Ames Research Center (ARC), and a Xeon Phi 7210 node at NASA Langley Research Center (LaRC)

Clonal heterogeneity as a driver of disease variability in the evolution of myeloproliferative neoplasms.

Myeloproliferative neoplasms (MPNs) are clonal hematological diseases in which cells of the myelo-erythroid lineage are overproduced and patients are predisposed to leukemic transformation. Hematopoietic stem cells are the suspected disease-initiating cells, and these cells must acquire a clonal advantage relative to nonmutant hematopoietic stem cells to perpetuate disease. In 2005, several groups identified a single gain-of-function point mutation in JAK2 that associated with the majority of MPNs, and subsequent studies have led to a comprehensive understanding of the mutational landscape in MPNs. However, confusion still exists as to how a single genetic aberration can be associated with multiple distinct disease entities. Many explanations have been proposed, including JAK2V617F homozygosity, individual patient heterogeneity, and the differential regulation of downstream JAK2 signaling pathways. Several groups have made knock-in mouse models expressing JAK2V617F and have observed divergent phenotypes, each recapitulating some aspects of disease. Intriguingly, most of these models do not observe a strong hematopoietic stem cell self-renewal advantage compared with wild-type littermate controls, raising the question of how a clonal advantage is established in patients with MPNs. This review summarizes the current molecular understanding of MPNs and the diversity of disease phenotypes and proposes that the increased proliferation induced by JAK2V617F applies a selection pressure on the mutant clone that results in highly diverse clonal evolution in individuals.This is the author's accepted manuscript. The final version of this paper is published in Experimental Hematology here: http://www.exphem.org/article/S0301-472X(14)00622-5/abstract

Determination of complex subclonal structures of hematological malignancies by multiplexed genotyping of blood progenitor colonies.

Current next-generation sequencing (NGS) technologies allow unprecedented insights into the mutational profiles of tumors. Recent studies in myeloproliferative neoplasms have further demonstrated that, not only the mutational profile, but also the order in which these mutations are acquired is relevant for our understanding of the disease. Our ability to assign mutation order from NGS data alone is, however, limited. Here, we present a strategy of highly multiplexed genotyping of burst forming unit-erythroid colonies based on NGS results to assess subclonal tumor structure. This allowed for the generation of complex clonal hierarchies and determination of order of mutation acquisition far more accurately than was possible from NGS data alone.Work in ARG lab has been supported by the Leukemia and Lymphoma Society (grant 7001-12), the National Institute of Health Research (grant NF-SI-0512-10079) and core support grants by the MRC and Wellcome Trust to the Cambridge Institute for Medical Research (100140/Z/12/Z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z). Work in ARG's laboratory has in addition been supported by Cancer Research UK (grants C1163/A12765 and C1163/A21762), Bloodwise (grant 13003) and the Wellcome Trust (grant 104710/Z/14/Z

HST STIS spectroscopy of the triple nucleus of M31: two nested disks in Keplerian rotation around a Supermassive Black Hole

We present HST spectroscopy of the nucleus of M31 obtained with STIS. Spectra taken around the CaT lines at 8500 see only the red giants in the double bright- ness peaks P1 and P2. In contrast, spectra taken at 3600-5100 A are sensitive to the tiny blue nucleus embedded in P2, the lower surface brightness red nucleus. P2 has a K-type spectrum, but the embedded blue nucleus has an A-type spectrum with strong Balmer absorption lines. Given the small likelihood for stellar collisions, a 200 Myr old starburst appears to be the most plausible origin of the blue nucleus. In stellar population, size, and velocity dispersion, the blue nucleus is so different from P1 and P2 that we call it P3. The line-of-sight velocity distributions of the red stars in P1+P2 strengthen the support for Tremaine s eccentric disk model. The kinematics of P3 is consistent with a circular stellar disk in Keplerian rotation around a super-massive black hole with M_bh = 1.4 x 10^8 M_sun. The P3 and the P1+P2 disks rotate in the same sense and are almost coplanar. The observed velocity dispersion of P3 is due to blurred rotation and has a maximum value of sigma = 1183+-201 km/s. The observed peak rotation velocity of P3 is V = 618+-81 km/s at radius 0.05" = 0.19 pc corresponding to a circular rotation velocity at this radius of ~1700 km/s. Any dark star cluster alternative to a black hole must have a half-mass radius <= 0.03" = 0.11 pc. We show that this excludes clusters of brown dwarfs or dead stars on astrophysical grounds.Comment: Astrophysical Journal, Sep 20, 2005, 21 pages including 20 figure

Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall A-level entry qualifications positively predicted performance during their first year and overall degree performance, but negatively predicted their performance during their third year. Additionally, and more specifically, students' A-level entry qualifications in Psychology positively predicted performance in the first year only. Such findings have implications for admissions tutors, as well as for students who have not studied Psychology before but who are considering applying to do so at university

The promise and peril of intensive-site-based ecological research: insights from the Hubbard Brook ecosystem study

Abstract. Ecological research is increasingly concentrated at particular locations or sites. This trend reflects a variety of advantages of intensive, site-based research, but also raises important questions about the nature of such spatially delimited research: how well does site based research represent broader areas, and does it constrain scientific discovery?We provide an overview of these issues with a particular focus on one prominent intensive research site: the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA. Among the key features of intensive sites are: long-term, archived data sets that provide a context for new discoveries and the elucidation of ecological mechanisms; the capacity to constrain inputs and parameters, and to validate models of complex ecological processes; and the intellectual cross-fertilization among disciplines in ecological and environmental sciences. The feasibility of scaling up ecological observations from intensive sites depends upon both the phenomenon of interest and the characteristics of the site. An evaluation of deviation metrics for the HBEF illustrates that, in some respects, including sensitivity and recovery of streams and trees from acid deposition, this site is representative of the Northern Forest region, of which HBEF is a part. However, the mountainous terrain and lack of significant agricultural legacy make the HBEF among the least disturbed sites in the Northern Forest region. Its relatively cool, wet climate contributes to high stream flow compared to other sites. These similarities and differences between the HBEF and the region can profoundly influence ecological patterns and processes and potentially limit the generality of observations at this and other intensive sites. Indeed, the difficulty of scaling up may be greatest for ecological phenomena that are sensitive to historical disturbance and that exhibit the greatest spatiotemporal variation, such as denitrification in soils and the dynamics of bird communities. Our research shows that end member sites for some processes often provide important insights into the behavior of inherently heterogeneous ecological processes. In the current era of rapid environmental and biological change, key ecological responses at intensive sites will reflect both specific local drivers and regional trends

Mutant CALR functions: gains and losses.

In this issue of Blood, Shide et al separate the roles of loss of a normal CALR allele and gain of a mutant CALR allele in CALR-driven essential thrombocythemia (ET)

Myeloproliferative neoplasms: from origins to outcomes.

Substantial progress has been made in our understanding of the pathogenetic basis of myeloproliferative neoplasms. The discovery of mutations in JAK2 over a decade ago heralded a new age for patient care as a consequence of improved diagnosis and the development of therapeutic JAK inhibitors. The more recent identification of mutations in calreticulin brought with it a sense of completeness, with most patients with myeloproliferative neoplasm now having a biological basis for their excessive myeloproliferation. We are also beginning to understand the processes that lead to acquisition of somatic mutations and the factors that influence subsequent clonal expansion and emergence of disease. Extended genomic profiling has established a multitude of additional acquired mutations, particularly prevalent in myelofibrosis, where their presence carries prognostic implications. A major goal is to integrate genetic, clinical, and laboratory features to identify patients who share disease biology and clinical outcome, such that therapies, both existing and novel, can be better targeted

The Superconducting Transition Temperatures of Fe1+xSe1--y, Fe1+xSe1--yTey and (K/Rb/Cs)zFe2--xSe2

In a recent contribution to this journal, it was shown that the transition temperatures of optimal high-Tc compounds obey the algebraic relation, Tc0 = kB-1{\beta}/\ell{\zeta}, where \ell is related to the mean spacing between interacting charges in the layers, {\zeta} is the distance between interacting electronic layers, {\beta} is a universal constant and kB is Boltzmann's constant. The equation was derived assuming pairing based on interlayer Coulomb interactions between physically separated charges. This theory was initially validated for 31 compounds from five different high-Tc families (within an accuracy of \pm1.37 K). Herein we report the addition of Fe1+xSe1-y and Fe1+xSe1-yTey (both optimized under pressure) and AzFe2-xSe2 (for A = K, Rb, or Cs) to the growing list of Coulomb-mediated superconducting compounds in which Tc0 is determined by the above equation. Doping in these materials is accomplished through the introduction of excess Fe and/or Se deficiency, or a combination of alkali metal and Fe vacancies. Consequently, a very small number of vacancies or interstitials can induce a superconducting state with a substantial transition temperature. The confirmation of the above equation for these Se-based Fe chalcogenides increases to six the number of superconducting families for which the transition temperature can be accurately predicted.Comment: 16 pages, 54 references 3 figures 1 tabl